Optical Flow Regularization of Implicit Neural Representations for Video Frame Interpolation [article]

Weihao Zhuang, Tristan Hascoet, Ryoichi Takashima, Tetsuya Takiguchi
2022 arXiv   pre-print
Recent works have shown the ability of Implicit Neural Representations (INR) to carry meaningful representations of signal derivatives. In this work, we leverage this property to perform Video Frame Interpolation (VFI) by explicitly constraining the derivatives of the INR to satisfy the optical flow constraint equation. We achieve state of the art VFI on limited motion ranges using only a target video and its optical flow, without learning the interpolation operator from additional training
more » ... . We further show that constraining the INR derivatives not only allows to better interpolate intermediate frames but also improves the ability of narrow networks to fit the observed frames, which suggests potential applications to video compression and INR optimization.
arXiv:2206.10886v1 fatcat:74a4s2rhknh2bnsyfofvbhtj2u